Developmental gene regulatory networks (GRNs) tie together low-level descriptions of molecular events into predictive high-level causal models of developmental processes. BioTapestry is a web-deployed, cross- platform application written in Java that we have developed to model developmental GRNs. Since its first public release in 2004, BioTapestry has become a de facto standard for developmental GRN modeling, and this proposal aims to enhance it in significant ways that will increase its utility and capabilities as research tool. The first goal, addressed in Aim 1, is to create a version of BioTapestry using emerging standard web browser and server technologies. These tools are increasingly becoming the norm for implementing integrated data analysis and interpretation applications across a wide range of biological research domains. Thus, by taking this browser-integrated approach for BioTapestry, it will become an important element of the growing toolkit of available techniques that are being combined together to build modern web interfaces for exploring and analyzing increasingly complex data sets. The second goal expands on BioTapestry's initial main focus as a tool for presenting and annotating a single, canonical, gold standard representation of a GRN model. Such models are the end result of a process that involves evaluating several alternative architectures and related dynamic network behaviors. By making specific targeted improvements to BioTapestry, we propose to greatly enhance this process of creating GRN models. In Aim 2, we will modify the BioTapestry core to provide a framework within which many different but related alternative GRN proposals can be organized, managed, and compared. This framework will then enable us, in Aim 3, to create an interactive computational environment within BioTapestry. This environment will enable the researcher to generate dynamic predictions of GRN behavior using a set of simplified yet powerful computational models. These predictions can then be compared directly against experimental data using new enhancements to BioTapestry's intuitive presentation of dynamic network behavior. At the conclusion of this project, we will have made BioTapestry into an even more effective system for modeling and analyzing GRNs.